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Techno-Economic Analysis Simplified: A Practical Guide for Macro Users

Authors

Hongxi Luo and Eric D. Larson

Andlinger Center for Energy and the Environment, Princeton University, Princeton, NJ 08540, USA

Background

This document provides high-level guidance and practical recommendations for Macro users who are new to techno-economic analysis, assisting them in extracting relevant techno-economic parameters from the literature for technology assets to be represented in Macro. While not required by Macro, it is strongly recommended that users carefully document the sources of the techno-economic parameters for all assets.

Example System

The Natural Gas Combined Cycle with carbon capture and storage (NGCC-CCS), categorized under "ThermalPowerCCS" in Macro, is used as the example, with the technical report "Cost and Performance Baseline for Fossil Energy Plants Volume 1: Bituminous Coal and Natural Gas to Electricity" from the National Energy Technology Laboratory (NETL) [1] serving as the primary reference. Tables and figures in this NETL report are labeled "Exhibits 1-1", "Exhibit 2-1", etc. and so will be referred to in this guide as "Ex 1-1", "Ex 2-1", etc.

System Description

The example has two significant components –- the NGCC power plant and the CCS facility.

  • The NGCC power plant features a 2×2×1 configuration, consisting of two F-class combustion turbine generators (CTGs), two heat recovery steam generators (HRSGs), and one steam turbine generator (STG).

  • The CCS facility captures 90% of the CO₂ from the flue gas exiting the HRSGs using the Cansolv (amine solvent) system, purifies it, and compresses it to conditions suitable for pipeline transportation.

Fuel Properties

Parameters related to fuel properties are "emission_rate" and "capture_rate".

  • Ex 2-6 provides the natural gas composition on a volumetric basis. Under standard conditions and assuming ideal gas behavior, the volumetric composition can be approximated by the molar composition. By applying the appropriate molecular weight (e.g., 16 kg/kmol for CH₄) and accounting for the atom balance (e.g., one carbon atom per CH₄ molecule), the CO₂ emissions embedded in natural gas (assuming eventual complete combustion) are 2.64 kg CO₂ per kg of natural gas, or 2.64 tonnes of CO₂ per tonne of natural gas.

  • Ex 2-6 provides the higher heating value (HHV) and lower heating value (LHV) of natural gas: 52,295 kJ/kg and 47,201 kJ/kg, respectively. Dividing these numbers by 3,600 to convert kJ/kg into MWh/tonne, the HHV and LHV of natural gas are 14.53 MWh/tonne and 13.11 MWh/tonne, respectively.

  • Based on the calculations above, the CO₂ emissions embedded in natural gas are 0.182 tonnes of CO₂ per MWh of natural gas (HHV basis) and 0.201 tonnes of CO₂ per MWh of natural gas (LHV basis). Upon complete combustion, all the CO₂ embedded in natural gas is converted to CO₂ in the flue gas, with 90% captured and 10% emitted.

  • The emission_rate for this asset in the Macro is 0.0182 tonnes of CO₂ per MWh of natural gas (HHV basis) or 0.0201 tonnes of CO₂ per MWh (LHV basis).

  • The capture_rate for this asset in the Macro is 0.1638 tonnes of CO₂ per MWh of natural gas (HHV basis) and 0.1809 tonnes of CO₂ per MWh (LHV basis).

Fuel Properties - Notes

  • The calculation method above relies on fuel composition and elemental balance, ensuring high analytical rigor. In cases where this information is unavailable, users can refer to well-established emission factors for fuels.

  • The calculations above reflect the emissions associated with natural gas consumption. However, emissions from natural gas extraction and transportation can also be significant and should be incorporated separately in other sections of the Macro model. These considerations apply equally to other fuels, including coal and biomass.

  • Users should recognize that CO₂ removal efficiency (e.g., 90% for the NGCC-CCS case) is specific to each technology asset and must ensure that an appropriate CO₂ removal efficiency is used when calculating both the emission_rate and the capture_rate.

Steady-state Operation

Key parameters for steady-state operations are "fuel_consumption" and "capacity_size".

  • Ex 5-23 shows that the NGCC-CCS facility has a net electric power output of 646 MWe. Hence, the capacity_size for this asset in the Macro is 646 MWe.

  • Ex 5-23 indicates that the net plant efficiency is 47.7% (HHV basis) and 52.8% (LHV basis). Therefore, the fuel_consumption (reciprocal of efficiency) for this asset in the Macro is 2.096 (HHV basis) or 1.894 (LHV basis).

Steady-state Operation - Notes

  • Within an asset, users must ensure that they input the emission_rate, capture_rate, and fuel_consumption using a consistent heating value basis, either LHV or HHV.

  • It is recommended that users use the capacity_size and fuel_consumption that are representative of the geographic region of interest. For technology assets expected to be deployed only in the future, it may be acceptable to use capacity_size and fuel_consumption projections from other regions if no specific values are available for the region of interest.

Project Economics

Parameters related to project economics are "investment_cost", "fixed_om_cost", "variable_om_cost" and fuel cost.

  • Ex 5-32 shows that the total as-spent cost (TASC) of the NGCC-CCS facility is $1,701,831,000 (in 2018 dollars). Dividing this by the facility's capacity (i.e., capacity_size) of 646 MWe yields a unit capacity investment of $2,634,413 per MWe (in 2018 dollars). Therefore, in the Macro model, the investment_cost for this asset is $2,634,413/MWe. If users instead wish to input an annualized_investment_cost, a capital recovery factor (e.g., 0.07 as recommended in another NETL report [2]) can be applied to the investment_cost, resulting in an annualized_investment_cost of $184,409/yr-MWe (in 2018 dollars) for this asset in the Macro model.

  • Ex 5-33 indicates that the annual fixed operating costs are $63.91 per year per kWe (in 2018 dollars). Therefore, the fixed_om_cost for this asset in the Macro model is $63,911/yr-MWe (in 2018 dollars).

  • Ex 5-33 shows that the variable operating costs (which excludes fuel costs) are $5.63 per MWh (in 2018 dollars). Hence, the variable_om_cost for this asset in the Macro model is $5.63/MWh (in 2018 dollars).

  • The study uses a natural gas price of $4.19 per GJ on an HHV basis (in 2018 dollars, as noted in the paragraph above Exhibit 2-6). As a result, users should input $15.08/MWh for all cells under "Time_Index" in the "fuel_price.csv" file.

Project Economics - Notes

  • Ideally, techno-economic parameters reported by studies that thoroughly discuss input data and assumptions should be prioritized. A good example of such studies, in the form of a journal article, is [3].

  • Users should carefully identify the underlying assumptions and considerations for capital cost estimates, such as which cost layers are included, how each cost layer is evaluated, and whether the project is first-of-its-kind or commercially mature, because these factors can significantly influence the final capital cost value. For example, in Ex 2-20 of the NETL report, the capital cost is divided into five layers, ranging from the bare-erected cost (BEC) to the total as-spent cost (TASC). In the case of the NGCC-CCS facility, the BEC, as shown in Ex 5-31, is $847,376,000 (in 2018 dollars). If this value is used instead of the TASC, the investment_cost for this asset in the Macro model would be $1,311,727/MWe (in 2018 dollars). In this case, understanding whether to use TASC or one of the other capital cost layers in the NETL report is the responsibility of the user.

  • Users should carefully identify the base year of the capital cost values (e.g., 2018 for the NGCC-CCS example) and ensure consistency in the base year used across different assets. If the base year differs between the collected values, appropriate indexes, such as the Chemical Engineering Plant Cost Index (CEPCI) [4] or its equivalent, should be referenced and applied to adjust all base years to a common desired base year.

  • Users should carefully identify the geographic region for which capital cost values are developed and always use values specific to the region of interest. If capital costs for the desired region are unavailable, location factors may be used to adjust values from another region [5]. Generally, it is inappropriate to apply capital cost values directly from one region to another.

  • Users should understand that once a capital cost value –- whether derived from real-world projects or engineering design studies –- is selected as a representative value for an asset in the Macro model, it becomes a user estimate. This estimate is unlikely to be more accurate than a Class IV estimate, as defined by the Association for the Advancement of Cost Engineering (AACE) [6], which has an uncertainty range of -30% to +50%. This range should be kept in mind when considering conducting sensitivity analysis on investment_cost values.

  • Users should recognize that the reported capital cost value typically corresponds to the capacity of a specific facility. If this capacity differs from the one of interest, e.g., if the available capital cost estimate is for a 300 MW NGCC plant, while most NGCC plants in the region of interest are 500 MW, a scaling method can be applied. Further details on how to properly conduct the scaling process can be found in a NETL report [7].

  • It is recommended that users obtain region- and technology-specific weighted-average cost of capital (WACC) [8], which forms a key part of the capital recovery factor (CRF) used to convert investment_cost into annualized_investment_cost. At a minimum, a region-specific, technology-agnostic WACC should be used.

  • The annual fixed operating costs (fixed_om_cost) typically include labor costs, maintenance costs, and property taxes and insurance. Apart from labor costs, the other expenses are generally estimated as a small percentage of the capital cost. Consequently, the base year of these costs should be adjusted in the same manner as capital costs, i.e., using the CEPCI or an equivalent index. For labor costs, statistics published by the Bureau of Labor (or equivalent organization in a region) could be consulted to determine an appropriate salary for asset operators in the desired base year.

  • Users should ensure that the annual variable operating costs (variable_om_cost) do not include fuel costs, as some studies combine them. Since the price of consumables can vary significantly, using a most recent 10-year average adjusted for inflation to reflect the desired base year is considered a reasonable approach.

References

1. James Iii, R.E., et al., Cost and performance baseline for fossil energy plants volume 1: bituminous coal and natural gas to electricity. 2019, National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV .... Available from: https://www.osti.gov/biblio/1569246

2. Theis, J., Quality Guidelines for Energy Systems Studies: Cost Estimation Methodology for NETL Assessments of Power Plant Performance. 2021: United States.

3. Luo, H., et al., Biopower with molten carbonate fuel cell carbon dioxide capture: Performance, cost, and grid-integration evaluations. Energy Conversion and Management, 2024. 322: p. 119167.

4. The Chemical Engineering Plant Cost Index. Chemical Engineering, 2023 [cited 2023 Feb 28]; Available from: https://www.chemengonline.com/pci-home.

5. Towler, G. and R. Sinnott, Chemical engineering design: principles, practice and economics of plant and process design. 2021: Butterworth-Heinemann.

6. Christensen, P., et al., Cost Estimate Classification system-as applied in engineering, procurement, and construction for the process industries. AACE International Recommended Practices, 2005: p. 1-30.

7. Zoelle, A. and N. Kuehn, Quality Guidelines for Energy System Studies: Capital Cost Scaling Methodology: Revision 4 Report. 2019, National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV ....

8. Davis, D. Methods, Assumptions, Scenarios & Sensitivities. Net Zero Australia 2023 [cited 2025 Jan, 2nd]; Available from: https://www.netzeroaustralia.net.au/wp-content/uploads/2023/04/Net-Zero-Australia-Methods-Assumptions-Scenarios-Sensitivities.pdf.